The official Python client library for Nucleus, the Data Platform for AI
Project description
Nucleus
https://dashboard.scale.com/nucleus
Aggregate metrics in ML are not good enough. To improve production ML, you need to understand their qualitative failure modes, fix them by gathering more data, and curate diverse scenarios.
Scale Nucleus helps you:
- Visualize your data
- Curate interesting slices within your dataset
- Review and manage annotations
- Measure and debug your model performance
Nucleus is a new way—the right way—to develop ML models, helping us move away from the concept of one dataset and towards a paradigm of collections of scenarios.
Installation
$ pip install scale-nucleus
Common issues/FAQ
Outdated Client
Nucleus is iterating rapidly and as a result we do not always perfectly preserve backwards compatibility with older versions of the client. If you run into any unexpected error, it's a good idea to upgrade your version of the client by running
pip install --upgrade scale-nucleus
Usage
For the most up to date documentation, reference: https://dashboard.scale.com/nucleus/docs/api?language=python.
For Developers
Clone from github and install as editable
git clone git@github.com:scaleapi/nucleus-python-client.git
cd nucleus-python-client
pip3 install poetry
poetry install
Please install the pre-commit hooks by running the following command:
poetry run pre-commit install
When releasing a new version please add release notes to the changelog in CHANGELOG.md
.
Best practices for testing: (1). Please run pytest from the root directory of the repo, i.e.
poetry run pytest tests/test_dataset.py
(2) To skip slow integration tests that have to wait for an async job to start.
poetry run pytest -m "not integration"
Updating documentation: We use Sphinx to autogenerate our API Reference from docstrings.
To test your local docstring changes, run the following commands from the repository's root directory:
poetry shell
cd docs
sphinx-autobuild . ./_build/html --watch ../nucleus
sphinx-autobuild
will spin up a server on localhost (port 8000 by default) that will watch for and automatically rebuild a version of the API reference based on your local docstring changes.
Project details
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